Overview

Dataset statistics

Number of variables17
Number of observations61
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.2 KiB
Average record size in memory138.2 B

Variable types

Text1
Numeric16

Alerts

AT is highly overall correlated with BE and 14 other fieldsHigh correlation
BE is highly overall correlated with AT and 14 other fieldsHigh correlation
DE is highly overall correlated with AT and 14 other fieldsHigh correlation
DK is highly overall correlated with AT and 14 other fieldsHigh correlation
ES is highly overall correlated with AT and 14 other fieldsHigh correlation
FI is highly overall correlated with AT and 14 other fieldsHigh correlation
FR is highly overall correlated with AT and 14 other fieldsHigh correlation
GB is highly overall correlated with AT and 14 other fieldsHigh correlation
IE is highly overall correlated with AT and 14 other fieldsHigh correlation
IT is highly overall correlated with AT and 14 other fieldsHigh correlation
NL is highly overall correlated with AT and 14 other fieldsHigh correlation
NO is highly overall correlated with AT and 14 other fieldsHigh correlation
PL is highly overall correlated with AT and 14 other fieldsHigh correlation
PT is highly overall correlated with AT and 14 other fieldsHigh correlation
SE is highly overall correlated with AT and 14 other fieldsHigh correlation
Total general is highly overall correlated with AT and 14 other fieldsHigh correlation
Fecha has unique valuesUnique
DE has unique valuesUnique
DK has unique valuesUnique
ES has unique valuesUnique
FI has unique valuesUnique
FR has unique valuesUnique
GB has unique valuesUnique
IE has unique valuesUnique
NO has unique valuesUnique
SE has unique valuesUnique
IT has unique valuesUnique
PL has unique valuesUnique
NL has unique valuesUnique
BE has unique valuesUnique
PT has unique valuesUnique
AT has unique valuesUnique
Total general has unique valuesUnique

Reproduction

Analysis started2024-02-11 16:34:55.286674
Analysis finished2024-02-11 16:35:43.559782
Duration48.27 seconds
Software versionydata-profiling v0.0.dev0
Download configurationconfig.json

Variables

Fecha
Text

UNIQUE 

Distinct61
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size620.0 B
2024-02-11T17:35:43.955144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length7
Mean length7.0983607
Min length7

Characters and Unicode

Total characters433
Distinct characters21
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique61 ?
Unique (%)100.0%

Sample

1st row2019-01
2nd row2019-02
3rd row2019-03
4th row2019-04
5th row2019-05
ValueCountFrequency (%)
2019-01 1
 
1.6%
2020-04 1
 
1.6%
2019-03 1
 
1.6%
2019-04 1
 
1.6%
2019-05 1
 
1.6%
2019-06 1
 
1.6%
2019-07 1
 
1.6%
2019-08 1
 
1.6%
2019-09 1
 
1.6%
2019-10 1
 
1.6%
Other values (52) 52
83.9%
2024-02-11T17:35:44.760777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 130
30.0%
0 122
28.2%
- 60
13.9%
1 49
 
11.3%
9 17
 
3.9%
3 17
 
3.9%
5 5
 
1.2%
6 5
 
1.2%
7 5
 
1.2%
4 5
 
1.2%
Other values (11) 18
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 360
83.1%
Dash Punctuation 60
 
13.9%
Lowercase Letter 11
 
2.5%
Uppercase Letter 1
 
0.2%
Space Separator 1
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 130
36.1%
0 122
33.9%
1 49
 
13.6%
9 17
 
4.7%
3 17
 
4.7%
5 5
 
1.4%
6 5
 
1.4%
7 5
 
1.4%
4 5
 
1.4%
8 5
 
1.4%
Lowercase Letter
ValueCountFrequency (%)
a 2
18.2%
l 2
18.2%
e 2
18.2%
o 1
9.1%
t 1
9.1%
g 1
9.1%
n 1
9.1%
r 1
9.1%
Dash Punctuation
ValueCountFrequency (%)
- 60
100.0%
Uppercase Letter
ValueCountFrequency (%)
T 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 421
97.2%
Latin 12
 
2.8%

Most frequent character per script

Common
ValueCountFrequency (%)
2 130
30.9%
0 122
29.0%
- 60
14.3%
1 49
 
11.6%
9 17
 
4.0%
3 17
 
4.0%
5 5
 
1.2%
6 5
 
1.2%
7 5
 
1.2%
4 5
 
1.2%
Other values (2) 6
 
1.4%
Latin
ValueCountFrequency (%)
a 2
16.7%
l 2
16.7%
e 2
16.7%
T 1
8.3%
o 1
8.3%
t 1
8.3%
g 1
8.3%
n 1
8.3%
r 1
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 433
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 130
30.0%
0 122
28.2%
- 60
13.9%
1 49
 
11.3%
9 17
 
3.9%
3 17
 
3.9%
5 5
 
1.2%
6 5
 
1.2%
7 5
 
1.2%
4 5
 
1.2%
Other values (11) 18
 
4.2%

DE
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct61
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1189812.3
Minimum199496
Maximum36289274
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size620.0 B
2024-02-11T17:35:45.074065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum199496
5-th percentile223789
Q1385493
median598902
Q3821835
95-th percentile992154
Maximum36289274
Range36089778
Interquartile range (IQR)436342

Descriptive statistics

Standard deviation4576233
Coefficient of variation (CV)3.8461807
Kurtosis60.591593
Mean1189812.3
Median Absolute Deviation (MAD)215576
Skewness7.7716254
Sum72578548
Variance2.0941908 Ɨ 1013
MonotonicityNot monotonic
2024-02-11T17:35:45.592765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
598902 1
 
1.6%
749712 1
 
1.6%
955265 1
 
1.6%
667194 1
 
1.6%
643582 1
 
1.6%
836163 1
 
1.6%
964275 1
 
1.6%
957493 1
 
1.6%
892808 1
 
1.6%
945776 1
 
1.6%
Other values (51) 51
83.6%
ValueCountFrequency (%)
199496 1
1.6%
207479 1
1.6%
219011 1
1.6%
223789 1
1.6%
227442 1
1.6%
239971 1
1.6%
254765 1
1.6%
255542 1
1.6%
258482 1
1.6%
259208 1
1.6%
ValueCountFrequency (%)
36289274 1
1.6%
1081438 1
1.6%
1054079 1
1.6%
992154 1
1.6%
978498 1
1.6%
964275 1
1.6%
957493 1
1.6%
955265 1
1.6%
945776 1
1.6%
926940 1
1.6%

DK
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct61
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean525447.67
Minimum25689
Maximum16026154
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size620.0 B
2024-02-11T17:35:45.836191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum25689
5-th percentile33529
Q1160715
median268207
Q3395136
95-th percentile468029
Maximum16026154
Range16000465
Interquartile range (IQR)234421

Descriptive statistics

Standard deviation2023858.7
Coefficient of variation (CV)3.8516845
Kurtosis60.22836
Mean525447.67
Median Absolute Deviation (MAD)126929
Skewness7.7372904
Sum32052308
Variance4.0960039 Ɨ 1012
MonotonicityNot monotonic
2024-02-11T17:35:46.180609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
411990 1
 
1.6%
249786 1
 
1.6%
264847 1
 
1.6%
247306 1
 
1.6%
230967 1
 
1.6%
400085 1
 
1.6%
326290 1
 
1.6%
366950 1
 
1.6%
422594 1
 
1.6%
468029 1
 
1.6%
Other values (51) 51
83.6%
ValueCountFrequency (%)
25689 1
1.6%
31983 1
1.6%
32862 1
1.6%
33529 1
1.6%
34814 1
1.6%
36136 1
1.6%
38400 1
1.6%
40124 1
1.6%
42611 1
1.6%
50983 1
1.6%
ValueCountFrequency (%)
16026154 1
1.6%
677899 1
1.6%
613434 1
1.6%
468029 1
1.6%
467978 1
1.6%
467813 1
1.6%
463254 1
1.6%
456848 1
1.6%
437989 1
1.6%
430949 1
1.6%

ES
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct61
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1396426.9
Minimum54770
Maximum42591021
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size620.0 B
2024-02-11T17:35:46.494554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum54770
5-th percentile118326
Q1255379
median681322
Q31172860
95-th percentile1745067
Maximum42591021
Range42536251
Interquartile range (IQR)917481

Descriptive statistics

Standard deviation5387269
Coefficient of variation (CV)3.8578954
Kurtosis59.821385
Mean1396426.9
Median Absolute Deviation (MAD)432797
Skewness7.6991505
Sum85182042
Variance2.9022667 Ɨ 1013
MonotonicityNot monotonic
2024-02-11T17:35:46.762154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
323062 1
 
1.6%
681322 1
 
1.6%
963903 1
 
1.6%
995483 1
 
1.6%
779637 1
 
1.6%
1211820 1
 
1.6%
1430095 1
 
1.6%
1745067 1
 
1.6%
1842830 1
 
1.6%
2006074 1
 
1.6%
Other values (51) 51
83.6%
ValueCountFrequency (%)
54770 1
1.6%
101643 1
1.6%
110100 1
1.6%
118326 1
1.6%
124071 1
1.6%
132414 1
1.6%
146987 1
1.6%
161544 1
1.6%
163264 1
1.6%
166809 1
1.6%
ValueCountFrequency (%)
42591021 1
1.6%
2006074 1
1.6%
1842830 1
1.6%
1745067 1
1.6%
1565329 1
1.6%
1430095 1
1.6%
1417030 1
1.6%
1411138 1
1.6%
1334593 1
1.6%
1274570 1
1.6%

FI
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct61
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean176541.93
Minimum11791
Maximum5384529
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size620.0 B
2024-02-11T17:35:47.039718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11791
5-th percentile13093
Q136106
median98060
Q3131985
95-th percentile173114
Maximum5384529
Range5372738
Interquartile range (IQR)95879

Descriptive statistics

Standard deviation679997.01
Coefficient of variation (CV)3.8517591
Kurtosis60.223476
Mean176541.93
Median Absolute Deviation (MAD)39643
Skewness7.7367318
Sum10769058
Variance4.6239593 Ɨ 1011
MonotonicityNot monotonic
2024-02-11T17:35:47.415854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
131985 1
 
1.6%
51629 1
 
1.6%
106223 1
 
1.6%
98060 1
 
1.6%
75469 1
 
1.6%
98170 1
 
1.6%
117447 1
 
1.6%
127816 1
 
1.6%
121109 1
 
1.6%
148108 1
 
1.6%
Other values (51) 51
83.6%
ValueCountFrequency (%)
11791 1
1.6%
12231 1
1.6%
13017 1
1.6%
13093 1
1.6%
13843 1
1.6%
13954 1
1.6%
15222 1
1.6%
15511 1
1.6%
18410 1
1.6%
18796 1
1.6%
ValueCountFrequency (%)
5384529 1
1.6%
179439 1
1.6%
177603 1
1.6%
173114 1
1.6%
172520 1
1.6%
169583 1
1.6%
162312 1
1.6%
159075 1
1.6%
158960 1
1.6%
148108 1
1.6%

FR
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct61
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean703553.51
Minimum32368
Maximum21458382
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size620.0 B
2024-02-11T17:35:47.796120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum32368
5-th percentile70034
Q1191450
median388177
Q3493721
95-th percentile762650
Maximum21458382
Range21426014
Interquartile range (IQR)302271

Descriptive statistics

Standard deviation2709122.1
Coefficient of variation (CV)3.8506269
Kurtosis60.297938
Mean703553.51
Median Absolute Deviation (MAD)138579
Skewness7.7438969
Sum42916764
Variance7.3393425 Ɨ 1012
MonotonicityNot monotonic
2024-02-11T17:35:48.166033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
388208 1
 
1.6%
472633 1
 
1.6%
493721 1
 
1.6%
419790 1
 
1.6%
298119 1
 
1.6%
426828 1
 
1.6%
648552 1
 
1.6%
762650 1
 
1.6%
768515 1
 
1.6%
852156 1
 
1.6%
Other values (51) 51
83.6%
ValueCountFrequency (%)
32368 1
1.6%
34987 1
1.6%
50380 1
1.6%
70034 1
1.6%
74268 1
1.6%
78090 1
1.6%
87537 1
1.6%
90320 1
1.6%
95553 1
1.6%
99674 1
1.6%
ValueCountFrequency (%)
21458382 1
1.6%
852156 1
1.6%
768515 1
1.6%
762650 1
1.6%
679944 1
1.6%
648552 1
1.6%
610370 1
1.6%
592489 1
1.6%
561238 1
1.6%
559392 1
1.6%

GB
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct61
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4237776.7
Minimum441189
Maximum1.2925219 Ɨ 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size620.0 B
2024-02-11T17:35:48.554489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum441189
5-th percentile524047
Q11353003
median2066543
Q33177875
95-th percentile4018639
Maximum1.2925219 Ɨ 108
Range1.28811 Ɨ 108
Interquartile range (IQR)1824872

Descriptive statistics

Standard deviation16311651
Coefficient of variation (CV)3.8491058
Kurtosis60.398196
Mean4237776.7
Median Absolute Deviation (MAD)1042657
Skewness7.7533843
Sum2.5850438 Ɨ 108
Variance2.6606995 Ɨ 1014
MonotonicityNot monotonic
2024-02-11T17:35:48.927928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2981446 1
 
1.6%
2075468 1
 
1.6%
1905136 1
 
1.6%
1558616 1
 
1.6%
1163157 1
 
1.6%
2467547 1
 
1.6%
2796251 1
 
1.6%
3240860 1
 
1.6%
3430856 1
 
1.6%
4813226 1
 
1.6%
Other values (51) 51
83.6%
ValueCountFrequency (%)
441189 1
1.6%
455674 1
1.6%
460030 1
1.6%
524047 1
1.6%
578920 1
1.6%
621895 1
1.6%
665282 1
1.6%
679295 1
1.6%
738734 1
1.6%
742666 1
1.6%
ValueCountFrequency (%)
129252189 1
1.6%
4813226 1
1.6%
4142340 1
1.6%
4018639 1
1.6%
3743642 1
1.6%
3702363 1
1.6%
3672768 1
1.6%
3664214 1
1.6%
3484528 1
1.6%
3447298 1
1.6%

IE
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct61
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean248441.77
Minimum17285
Maximum7577474
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size620.0 B
2024-02-11T17:35:49.329849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum17285
5-th percentile24180
Q194671
median139705
Q3176097
95-th percentile217687
Maximum7577474
Range7560189
Interquartile range (IQR)81426

Descriptive statistics

Standard deviation956243.53
Coefficient of variation (CV)3.8489644
Kurtosis60.407607
Mean248441.77
Median Absolute Deviation (MAD)44318
Skewness7.7541107
Sum15154948
Variance9.1440168 Ɨ 1011
MonotonicityNot monotonic
2024-02-11T17:35:49.694339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
175714 1
 
1.6%
107739 1
 
1.6%
105191 1
 
1.6%
101729 1
 
1.6%
95387 1
 
1.6%
176097 1
 
1.6%
190695 1
 
1.6%
221082 1
 
1.6%
214992 1
 
1.6%
225007 1
 
1.6%
Other values (51) 51
83.6%
ValueCountFrequency (%)
17285 1
1.6%
19406 1
1.6%
23527 1
1.6%
24180 1
1.6%
24768 1
1.6%
26328 1
1.6%
27162 1
1.6%
27831 1
1.6%
28048 1
1.6%
30953 1
1.6%
ValueCountFrequency (%)
7577474 1
1.6%
225007 1
1.6%
221082 1
1.6%
217687 1
1.6%
217648 1
1.6%
214992 1
1.6%
212844 1
1.6%
211553 1
1.6%
209123 1
1.6%
206441 1
1.6%

NO
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct61
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean293263.18
Minimum19194
Maximum8944527
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size620.0 B
2024-02-11T17:35:50.010784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19194
5-th percentile21382
Q171775
median141111
Q3212204
95-th percentile308549
Maximum8944527
Range8925333
Interquartile range (IQR)140429

Descriptive statistics

Standard deviation1130081.5
Coefficient of variation (CV)3.8534723
Kurtosis60.110862
Mean293263.18
Median Absolute Deviation (MAD)69533
Skewness7.7263149
Sum17889054
Variance1.2770843 Ɨ 1012
MonotonicityNot monotonic
2024-02-11T17:35:50.271004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
200472 1
 
1.6%
108536 1
 
1.6%
138387 1
 
1.6%
152289 1
 
1.6%
139747 1
 
1.6%
197923 1
 
1.6%
212204 1
 
1.6%
240606 1
 
1.6%
294271 1
 
1.6%
376816 1
 
1.6%
Other values (51) 51
83.6%
ValueCountFrequency (%)
19194 1
1.6%
21183 1
1.6%
21313 1
1.6%
21382 1
1.6%
21454 1
1.6%
22359 1
1.6%
22378 1
1.6%
24796 1
1.6%
25076 1
1.6%
25520 1
1.6%
ValueCountFrequency (%)
8944527 1
1.6%
376816 1
1.6%
366025 1
1.6%
308549 1
1.6%
294280 1
1.6%
294271 1
1.6%
290905 1
1.6%
289742 1
1.6%
272845 1
1.6%
262101 1
1.6%

SE
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct61
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean889152.85
Minimum38866
Maximum27119162
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size620.0 B
2024-02-11T17:35:50.600613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum38866
5-th percentile72633
Q1217107
median458261
Q3637241
95-th percentile943107
Maximum27119162
Range27080296
Interquartile range (IQR)420134

Descriptive statistics

Standard deviation3428111.5
Coefficient of variation (CV)3.8554805
Kurtosis59.979175
Mean889152.85
Median Absolute Deviation (MAD)201757
Skewness7.7144018
Sum54238324
Variance1.1751949 Ɨ 1013
MonotonicityNot monotonic
2024-02-11T17:35:50.983071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
464585 1
 
1.6%
294913 1
 
1.6%
326452 1
 
1.6%
274143 1
 
1.6%
217107 1
 
1.6%
384484 1
 
1.6%
434411 1
 
1.6%
451554 1
 
1.6%
641655 1
 
1.6%
772907 1
 
1.6%
Other values (51) 51
83.6%
ValueCountFrequency (%)
38866 1
1.6%
48622 1
1.6%
68652 1
1.6%
72633 1
1.6%
76920 1
1.6%
78298 1
1.6%
78588 1
1.6%
89897 1
1.6%
94100 1
1.6%
95858 1
1.6%
ValueCountFrequency (%)
27119162 1
1.6%
1570427 1
1.6%
1352780 1
1.6%
943107 1
1.6%
850459 1
1.6%
838756 1
1.6%
796349 1
1.6%
780516 1
1.6%
772907 1
1.6%
719037 1
1.6%

IT
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct61
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean935496.95
Minimum28554
Maximum28532657
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size620.0 B
2024-02-11T17:35:51.313806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum28554
5-th percentile74188
Q1287716
median451523
Q3706786
95-th percentile1012989
Maximum28532657
Range28504103
Interquartile range (IQR)419070

Descriptive statistics

Standard deviation3605025.8
Coefficient of variation (CV)3.8535944
Kurtosis60.102842
Mean935496.95
Median Absolute Deviation (MAD)255263
Skewness7.725582
Sum57065314
Variance1.2996211 Ɨ 1013
MonotonicityNot monotonic
2024-02-11T17:35:51.604188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
460603 1
 
1.6%
364678 1
 
1.6%
590521 1
 
1.6%
546269 1
 
1.6%
451523 1
 
1.6%
551417 1
 
1.6%
861090 1
 
1.6%
1012989 1
 
1.6%
1180018 1
 
1.6%
1262236 1
 
1.6%
Other values (51) 51
83.6%
ValueCountFrequency (%)
28554 1
1.6%
49056 1
1.6%
71264 1
1.6%
74188 1
1.6%
79755 1
1.6%
83480 1
1.6%
86171 1
1.6%
88145 1
1.6%
89923 1
1.6%
94008 1
1.6%
ValueCountFrequency (%)
28532657 1
1.6%
1262236 1
1.6%
1180018 1
1.6%
1012989 1
1.6%
968493 1
1.6%
935400 1
1.6%
872110 1
1.6%
861090 1
1.6%
796103 1
1.6%
783951 1
1.6%

PL
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct61
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean273306.3
Minimum7995
Maximum8335842
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size620.0 B
2024-02-11T17:35:51.903200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7995
5-th percentile26470
Q171028
median100465
Q3236825
95-th percentile333049
Maximum8335842
Range8327847
Interquartile range (IQR)165797

Descriptive statistics

Standard deviation1054103.9
Coefficient of variation (CV)3.8568592
Kurtosis59.889006
Mean273306.3
Median Absolute Deviation (MAD)69679
Skewness7.7055473
Sum16671684
Variance1.111135 Ɨ 1012
MonotonicityNot monotonic
2024-02-11T17:35:52.188397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
161883 1
 
1.6%
91882 1
 
1.6%
110431 1
 
1.6%
103123 1
 
1.6%
90156 1
 
1.6%
117721 1
 
1.6%
123844 1
 
1.6%
172675 1
 
1.6%
211711 1
 
1.6%
257449 1
 
1.6%
Other values (51) 51
83.6%
ValueCountFrequency (%)
7995 1
1.6%
10589 1
1.6%
25060 1
1.6%
26470 1
1.6%
26631 1
1.6%
27711 1
1.6%
30062 1
1.6%
30786 1
1.6%
31774 1
1.6%
35075 1
1.6%
ValueCountFrequency (%)
8335842 1
1.6%
342619 1
1.6%
337008 1
1.6%
333049 1
1.6%
317368 1
1.6%
290713 1
1.6%
286128 1
1.6%
284921 1
1.6%
276215 1
1.6%
262750 1
1.6%

NL
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct61
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean292891.48
Minimum13635
Maximum8933190
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size620.0 B
2024-02-11T17:35:52.520856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum13635
5-th percentile35666
Q1100491
median148103
Q3195484
95-th percentile272407
Maximum8933190
Range8919555
Interquartile range (IQR)94993

Descriptive statistics

Standard deviation1127181.5
Coefficient of variation (CV)3.8484612
Kurtosis60.44075
Mean292891.48
Median Absolute Deviation (MAD)47612
Skewness7.7574013
Sum17866380
Variance1.2705381 Ɨ 1012
MonotonicityNot monotonic
2024-02-11T17:35:52.930428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
144307 1
 
1.6%
121983 1
 
1.6%
117921 1
 
1.6%
124961 1
 
1.6%
117291 1
 
1.6%
152103 1
 
1.6%
169303 1
 
1.6%
204795 1
 
1.6%
195484 1
 
1.6%
186683 1
 
1.6%
Other values (51) 51
83.6%
ValueCountFrequency (%)
13635 1
1.6%
20281 1
1.6%
34599 1
1.6%
35666 1
1.6%
37938 1
1.6%
40570 1
1.6%
41192 1
1.6%
47267 1
1.6%
56750 1
1.6%
63591 1
1.6%
ValueCountFrequency (%)
8933190 1
1.6%
293739 1
1.6%
286150 1
1.6%
272407 1
1.6%
272157 1
1.6%
270934 1
1.6%
265376 1
1.6%
265134 1
1.6%
262096 1
1.6%
250391 1
1.6%

BE
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct61
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean223402.13
Minimum24814
Maximum6813765
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size620.0 B
2024-02-11T17:35:53.236299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum24814
5-th percentile31603
Q194247
median123923
Q3148332
95-th percentile168620
Maximum6813765
Range6788951
Interquartile range (IQR)54085

Descriptive statistics

Standard deviation858998.3
Coefficient of variation (CV)3.8450766
Kurtosis60.664831
Mean223402.13
Median Absolute Deviation (MAD)28659
Skewness7.7784564
Sum13627530
Variance7.3787809 Ɨ 1011
MonotonicityNot monotonic
2024-02-11T17:35:53.615939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
110488 1
 
1.6%
131814 1
 
1.6%
142382 1
 
1.6%
119342 1
 
1.6%
104622 1
 
1.6%
127275 1
 
1.6%
139253 1
 
1.6%
148332 1
 
1.6%
162678 1
 
1.6%
168620 1
 
1.6%
Other values (51) 51
83.6%
ValueCountFrequency (%)
24814 1
1.6%
28763 1
1.6%
30927 1
1.6%
31603 1
1.6%
31728 1
1.6%
32793 1
1.6%
33635 1
1.6%
34526 1
1.6%
49210 1
1.6%
50864 1
1.6%
ValueCountFrequency (%)
6813765 1
1.6%
176269 1
1.6%
172708 1
1.6%
168620 1
1.6%
167730 1
1.6%
162678 1
1.6%
160338 1
1.6%
159754 1
1.6%
159211 1
1.6%
158222 1
1.6%

PT
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct61
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean219768.43
Minimum9456
Maximum6702937
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size620.0 B
2024-02-11T17:35:54.001676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9456
5-th percentile15748
Q157365
median110522
Q3177988
95-th percentile221235
Maximum6702937
Range6693481
Interquartile range (IQR)120623

Descriptive statistics

Standard deviation846680.54
Coefficient of variation (CV)3.8526032
Kurtosis60.167966
Mean219768.43
Median Absolute Deviation (MAD)58251
Skewness7.7315504
Sum13405874
Variance7.1686793 Ɨ 1011
MonotonicityNot monotonic
2024-02-11T17:35:54.331605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
52165 1
 
1.6%
156886 1
 
1.6%
151432 1
 
1.6%
156939 1
 
1.6%
141362 1
 
1.6%
188548 1
 
1.6%
180451 1
 
1.6%
192092 1
 
1.6%
201034 1
 
1.6%
220452 1
 
1.6%
Other values (51) 51
83.6%
ValueCountFrequency (%)
9456 1
1.6%
10056 1
1.6%
15214 1
1.6%
15748 1
1.6%
17065 1
1.6%
20016 1
1.6%
22915 1
1.6%
24083 1
1.6%
24726 1
1.6%
25125 1
1.6%
ValueCountFrequency (%)
6702937 1
1.6%
225165 1
1.6%
224918 1
1.6%
221235 1
1.6%
220452 1
1.6%
209990 1
1.6%
207035 1
1.6%
205675 1
1.6%
201034 1
1.6%
192092 1
1.6%

AT
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct61
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean111031.54
Minimum6888
Maximum3386462
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size620.0 B
2024-02-11T17:35:54.661756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6888
5-th percentile10999
Q129544
median53485
Q384827
95-th percentile109581
Maximum3386462
Range3379574
Interquartile range (IQR)55283

Descriptive statistics

Standard deviation427710.11
Coefficient of variation (CV)3.8521497
Kurtosis60.197745
Mean111031.54
Median Absolute Deviation (MAD)31182
Skewness7.7344074
Sum6772924
Variance1.8293594 Ɨ 1011
MonotonicityNot monotonic
2024-02-11T17:35:55.187075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
44456 1
 
1.6%
58138 1
 
1.6%
78905 1
 
1.6%
77454 1
 
1.6%
84613 1
 
1.6%
93232 1
 
1.6%
94387 1
 
1.6%
103215 1
 
1.6%
93449 1
 
1.6%
98673 1
 
1.6%
Other values (51) 51
83.6%
ValueCountFrequency (%)
6888 1
1.6%
8642 1
1.6%
9196 1
1.6%
10999 1
1.6%
11574 1
1.6%
11858 1
1.6%
12945 1
1.6%
13373 1
1.6%
15728 1
1.6%
15738 1
1.6%
ValueCountFrequency (%)
3386462 1
1.6%
124247 1
1.6%
122215 1
1.6%
109581 1
1.6%
104716 1
1.6%
104049 1
1.6%
103215 1
1.6%
98673 1
1.6%
94387 1
1.6%
94163 1
1.6%

Total general
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct61
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11716314
Minimum1264727
Maximum3.5734756 Ɨ 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size620.0 B
2024-02-11T17:35:55.508456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1264727
5-th percentile1306705
Q13987890
median6594268
Q37750035
95-th percentile10674004
Maximum3.5734756 Ɨ 108
Range3.5608284 Ɨ 108
Interquartile range (IQR)3762145

Descriptive statistics

Standard deviation45086621
Coefficient of variation (CV)3.8481917
Kurtosis60.458591
Mean11716314
Median Absolute Deviation (MAD)2094280
Skewness7.759014
Sum7.1469513 Ɨ 108
Variance2.0328034 Ɨ 1015
MonotonicityNot monotonic
2024-02-11T17:35:55.772490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6650266 1
 
1.6%
5717119 1
 
1.6%
6450717 1
 
1.6%
5642698 1
 
1.6%
4632739 1
 
1.6%
7429413 1
 
1.6%
8688548 1
 
1.6%
9948176 1
 
1.6%
10674004 1
 
1.6%
12802212 1
 
1.6%
Other values (51) 51
83.6%
ValueCountFrequency (%)
1264727 1
1.6%
1266036 1
1.6%
1278431 1
1.6%
1306705 1
1.6%
1420676 1
1.6%
1441656 1
1.6%
1547653 1
1.6%
1576316 1
1.6%
1577908 1
1.6%
1677956 1
1.6%
ValueCountFrequency (%)
357347565 1
1.6%
12802212 1
1.6%
11075956 1
1.6%
10674004 1
1.6%
10375011 1
1.6%
9948176 1
1.6%
9867212 1
1.6%
9832240 1
1.6%
9448073 1
1.6%
9155210 1
1.6%

Interactions

2024-02-11T17:35:39.871671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:56.088849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:58.655346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:01.986149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:04.537163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:07.122417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:09.820717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:12.798476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:16.588163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:19.650701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:22.262181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:24.969367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:27.548419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:30.433856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:33.830820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:36.717077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:40.050037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:56.315088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:58.852808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:02.160952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:04.706563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:07.267320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:10.031032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:13.021523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:16.804579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:19.846326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:22.457400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:25.143007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:27.728082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:30.590935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:34.035232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:36.891617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:40.232191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:56.493944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:59.051845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:02.366454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:04.891575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:07.439977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:10.235820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:13.291684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:17.016644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:20.040595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:22.652549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:25.357364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:27.940689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:30.814911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:34.258294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:37.059942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:40.347498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:56.622617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:34:59.211854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:02.499780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:05.196951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
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2024-02-11T17:35:30.249745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:33.617255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:36.492191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-11T17:35:39.707452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-02-11T17:35:56.012389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ATBEDEDKESFIFRGBIEITNLNOPLPTSETotal general
AT1.0000.6510.8370.8770.9510.8510.8780.5190.6430.9130.8240.8800.9030.8890.8060.869
BE0.6511.0000.7340.6490.7250.6670.7960.8080.7790.7860.8150.7520.7480.8070.7470.839
DE0.8370.7341.0000.7920.8710.7770.9440.5960.6490.8680.7230.7970.8280.8750.7090.831
DK0.8770.6490.7921.0000.8760.9150.8480.6820.7830.8850.7840.9400.8990.7770.8910.910
ES0.9510.7250.8710.8761.0000.8480.9420.5780.6940.9480.8190.8820.8850.9130.8080.906
FI0.8510.6670.7770.9150.8481.0000.8270.6980.7780.8900.7930.9180.8990.7560.9070.902
FR0.8780.7960.9440.8480.9420.8271.0000.6490.7140.9450.7960.8660.8800.9290.7890.908
GB0.5190.8080.5960.6820.5780.6980.6491.0000.9260.6670.5980.7280.5990.5630.6790.797
IE0.6430.7790.6490.7830.6940.7780.7140.9261.0000.7670.6960.8130.6690.6320.7420.859
IT0.9130.7860.8680.8850.9480.8900.9450.6670.7671.0000.8660.9410.9250.9130.8700.956
NL0.8240.8150.7230.7840.8190.7930.7960.5980.6960.8661.0000.8470.8960.8520.8790.877
NO0.8800.7520.7970.9400.8820.9180.8660.7280.8130.9410.8471.0000.9220.8350.9150.958
PL0.9030.7480.8280.8990.8850.8990.8800.5990.6690.9250.8960.9221.0000.8910.9260.912
PT0.8890.8070.8750.7770.9130.7560.9290.5630.6320.9130.8520.8350.8911.0000.7850.868
SE0.8060.7470.7090.8910.8080.9070.7890.6790.7420.8700.8790.9150.9260.7851.0000.909
Total general0.8690.8390.8310.9100.9060.9020.9080.7970.8590.9560.8770.9580.9120.8680.9091.000

Missing values

2024-02-11T17:35:42.832069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-02-11T17:35:43.384207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

FechaDEDKESFIFRGBIENOSEITPLNLBEPTATTotal general
02019-01598902411990323062131985388208298144617571420047246458546060316188314430711048852165444566650266
12019-025470624114503319891181912953812670078175782167577488772344018105525811827087357040413295906249
22019-035896664379893807921293993795002896715202368185364541335444473878321155099424782651442416612081
32019-045368343201533788219325234344831114952176481407014242444477998311214810312606882387391946493259
42019-055737692781753694217673435764136727682115531382164756364217838348417300914469086721377367101336
52019-065290842153533450217388733976933286602091231528224112445079498074017119814102271817345236612212
62019-0750502426415939501788311382599348452819076011700946760847629510046515481115678269906330176886291
72019-0848567324109539096710335437702532347021563541223694717203189877795512498014560768576295446348908
82019-094537121989043095668718924334923722711225461251044121853288987367612210213223360368282595070362
92019-104587301607153213077383519145018587241227581131104646103131496790813123412392362144306884494285
FechaDEDKESFIFRGBIENOSEITPLNLBEPTATTotal general
512023-0410540793621509726751465925593923177875167825272845838756872110333049250391157034207035762659448073
522023-059921543275547934131306175612382379614149394214242719037783852284921238299159211191203689097993658
532023-069011013056229692681109025220861657232141086165259595626706786249611247189143838209990674116993007
542023-0770532935584813345931145155082021928832154190223963660018737900256244293739172708224918790367750035
552023-08775824345772117286012237047678118325111417191854956100456788612539512709341566412212351040497349048
562023-09726662303338120028515907543583314525361366561620105560256580262368252724071208231859121047166711129
572023-10646514395136141703013770348022213530031528031910339431077961032861282653761264631885011222157501337
582023-115969246134341265724135600417025171088013600036602515704277479892907132651341206201603051242478521047
592023-125803156778991257105130351408637182694011552729428013527807200223426192861501250051687731095818395984
60Total general36289274160261544259102153845292145838212925218975774748944527271191622853265783358428933190681376567029373386462357347565